祁连山区植被净初级生产力的空间变化特征分析

基于MODIS数据分析了2000~2010年祁连山区植被净初级生产力(Net Primary Productivity,NPP)的空间变化特征。结果显示:祁连山区植被NPP并不高,多年平均植被NPP仅为121.95gC/(m2·a),自东向西植被NPP逐渐减少。不同植被类型其NPP具有明显差异,大体上为:常绿阔叶林平原草地常绿针叶林典型草地农田高寒草甸草地荒漠草地落叶针叶林。祁连山区植被NPP变化在区域间也存在差异。植被NPP呈增长趋势的地区主要分布在青海年南山、拉脊山、达坂山和青海湖及其西侧,约占47.30%;乌鞘岭东部及以东的地区(约占1.97%)植被NPP呈减少趋势。降水是祁连山区植被NPP变化的主要因素,气温对植被NPP的影响并不明显,不合理的人类活动可能是造成部分区域植被NPP减少的重要原因。     

藏北中部地区草地退化遥感监测

为了探讨藏北中部地区近20年来的草地退化状况及主要驱动力,基于1990、2000及2010年的Landsat影像,采用混合分类方法对研究区主要景观类型进行分类,并利用景观指数分析景观格局及草地退化特征。另外,基于气象数据,利用灰色关联度方法分析草地退化的主要驱动力。结果表明:草地退化面积在1990~2000年呈增加趋势,在2000~2010年呈减少趋势,2000年之后研究区草地退化状况趋于缓和。造成草地退化的主要气候因素为降水量、气温、日照时数、平均相对湿度和蒸发量等,其中,高寒草甸草地主要受平均相对湿度及降水量的影响,高寒草原草地受蒸发量、日照时数、平均最低气温、降水量、平均相对湿度和平均最高气温的影响均较大,高寒荒漠草地与平均最高气温、日照时数和蒸发量的关系最为密切。     

若尔盖高原区域碳收支参量多尺度遥感综合观测试验:科学目标与试验设计

介绍了若尔盖高原区域碳收支参量多尺度遥感综合观测试验的研究背景、科学目标、关键问题、观测方案、观测系统设置和后续观测计划.总体目标是,开展若尔盖高原区域湿地-草地生态系统碳收支参量多尺度遥感与地面同步观测试验,为人为干扰条件下湿地-草地生态系统碳收支变化过程研究积累基础数据;发展能够融合多源、多尺度遥感观测的碳收支相关参量反演模型,为实现卫星遥感对区域尺度碳收支研究提供方法和范例;建立区域尺度上的多尺度观测体系,通过多源遥感技术与生态过程模型的耦合,降低碳收支遥感监测及模拟的不确定性,更加综合地理解湿地-草地生态系统不同时空尺度上的碳收支过程;增强遥感技术在湿地生态研究的应用性,并最终为区域湿地保护提供重要依据.试验以人为干扰剧烈的若尔盖高原湿地-草地区域为试验区,以碳循环过程的关键参量为主要观测对象,利用卫星遥感、航空遥感、地基遥感、通量观测、生态观测等相关设备,开展航空、卫星和地面配合的大型综合观测试验,精细化观测若尔盖高原沼泽化草甸、湿草甸、草甸、草原等不同覆被类型的碳收支过程的各个分量.讨论了碳收支参量的多尺度观测与时空尺度扩展问题,展望了同步综合观测试验在陆地生态系统碳循环研究的应用前景.     

呼伦贝尔生态环境遥感调查和驱动力分析

针对典型区的生态遥感监测的需要,采用RS、GIS一体化信息提取技术和数理统计方法,对呼伦贝尔地区进行了森林-草原生态交错带多时相遥感数据分析研究,揭示了研究区土地覆盖和生态要素结构变化、生态脆弱特征及时空分布规律,并以量化和可视化的形式反映了该地区生态环境现状及其变化。结果表明,近16年来该地区的生态质量在不断下降,草地退化和荒漠化的范围在扩大,生态环境形势严峻。人口增长和超载放牧是土地利用变化的主要原因。     

基于NDVI及DEM的青海湖北岸景观格局空间自相关分析

本文以青海湖北岸为研究区,利用2006年Landsat-5 TM数据,结合植被类型图、SRTM高程数据、1∶5万地形图等数据,获取了该区12类景观类型,分类总体精度为82.91%,Kappa系数为0.81。以NDVI均值、坡向均值、高程均值为区域观测值,计算研究区景观类型的空间自相关性的Moran指数,再根据局部Moran指数的空间集聚分布特征,分析这些景观类型之间的结构稳定性,表现为如下特征:第一,较稳定景观,格局类型包括河谷灌丛、山地灌丛、高寒沼泽、高寒草甸、河流、裸岩;第二,欠稳定景观,格局类型包括湖泊、温性草原、湖滨沼泽;第三,极不稳定景观,格局类型有沙地、石砾地、裸土地,如鸟岛、金沙湾,尕海地区的沙地。     

基于HJ-1A高光谱数据的藏北高原草地分类方法对比

环境减灾星星座A星（HJ 1A）携带的超光谱仪填补了我国星载高光谱影像采集领域的空白,但目前国内关于该高光谱数据的应用较少。本文基于HJ 1A高光谱(HSI)数据预处理技术,以申扎县北部为研究区,采用SPCA MLC和HSI SAM分类方法,结合野外实测样本,将研究区分为沼泽草甸、高寒草甸、高寒草原、荒漠化草原和裸地5种类型,并结合分类精度和分类图对2种分类方法进行了对比分析,可得基于HJ 1A高光谱数据的藏北高原草地分类方法中SPCA MLC法优于HSI SAM法。2种方法的分类精度皆大于80%,证明了HJ 1A的HSI数据在实现藏北草地高精度分类方面的巨大潜力。     

Investigating the spectral and ecological characteristics of grassland communities across an ecological gradient of the Inner Mongolian grasslands with in situ hyperspectral data

Grassland degradation is serious in the Mongolian plateau, especially in Inner Mongolia, China. Accurate monitoring of grassland types and qualities is increasingly important for the purposes of grassland conservation and restoration. Using in situ hyperspectral reflectance data and ground-based ecological measurements, we explored the potential for large-scale monitoring grassland communities using imaging spectroradiometers. We compared the spectral reflectance of the major types of grasslands and field plots with/without livestock grazing. We also did statistical analysis about the relationship between hyperspectral indices and aboveground biomass (AGB) of the surveyed grassland communities. The results showed that: (1) the dominant plant species varied across meadow, typical, and desert steppe, and they also varied between fenced and grazed plots; (2) in situ hyperspectral data are useful for differentiating grassland communities of meadow, typical, and desert steppe and grassland communities with and without livestock grazing; and (3) the prediction accuracies of vegetation indices for AGB decreased from desert to typical and meadow steppe, and the results were contrary for the prediction accuracies of red edge inflection point (REIP). REIP may not be suitable for estimating AGB of the low-density grassland communities. The above results implied that care must be taken while using statistical models to link spectral and ecological measurements in large geographical scales since there is lack of portability over different types of grassland communities. This study provides foundations for future large-scale efforts of monitoring grassland communities in Inner Mongolia using imaging spectroradiometers.     

Classification management for grassland using MODIS data: a case study in the Gannan region,China

Classification of grasslands is a convenient method to measure and manage the sustainability of Chinese grasslands. In this study, a timely and reliable procedure was examined using remote-sensing (RS) techniques. Linear regression analysis between field survey data and Moderate-Resolution Imaging Spectroradiometer (MODIS) data showed that among 17 vegetation indices (VIs) evaluated, the enhanced vegetation index (EVI) was the best VI to simulate forage dry biomass and cover in the Gannan region. The results of precision estimation of the models showed that power and logarithm regression satisfactorily simulated grassland dry biomass and grassland cover, respectively. The index of classification management of grasslands (ICGs) was used to subdivide grasslands into conservation grasslands and moderately productive grasslands in the Gannan region, where no grasslands fell into intensively productive grasslands. Conservation grasslands accounted for 2.04% of the available grasslands, whereas moderately productive grasslands were 97.96% of the available grasslands, and this is related to the history of the grasslands’ use and the per capita income in the Gannan region. This study proposes that the area of conservation grasslands and that of moderately productive grasslands are determined by increases in per capita income and changes in the human use of grasslands.     

Comparison of two inversion methods for leaf area index using HJ-1 satellite data in a temperate meadow steppe

Leaf area index (LAI) is one of the most important parameters for determining grassland canopy conditions. LAI controls numerous biological and physical processes in grassland ecosystems. Remote-sensing techniques are effective for estimating grassland LAI at a regional scale. Comparison of LAI inversion methods based on remote sensing is significant for accurate estimation of LAI in particular areas. In this study, we developed and compared two inversion models to estimate the LAI of a temperate meadow steppe in Hulunbuir, Inner Mongolia, China, based on HJ-1 satellite data and field-measured LAI data. LAI was measured from early June to late August in 2013, obtained from 326 sampling data. The back propagation (BP) neural network method proved better than the statistical regression model for estimating grassland LAI, the accuracy of the former being 82.8%. We then explored the spatio-temporal distribution in LAI of Stipa baicalensis Roshev. in the meadow steppe of Hulunbuir, including cut, grazed, and fenced plots. The LAI in the cut and grazed plots reflected the growth variations in S. baicalensis Roshev. However, because of the obvious litter layer, the LAI in the fenced plots was underestimated.     

结合遥感和统计数据的家畜分布网格化方法研究

家畜的空间分布对于粮食安全、农业社会经济、环境影响评估和人畜共患病的研究等方面至关重要.选取甘肃省作为典型研究区,以羊为研究对象,基于随机森林回归算法构建了融合遥感数据和统计数据的家畜分布网格化估算模型,获得甘肃省1 km×1 km尺度上羊的空间分布信息.结果表明:基于随机森林回归的家畜分布网格化估算模型,结合了遥感数...     

Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China

Water use efficiency (WUE) has been recognized as a crucial parameter to describe the interrelationship between carbon and water cycling. Quantitative assessment to spatiotemporal dynamics of ecosystem WUE in grasslands is of vital importance, given the large proportion of grasslands on the Earth’s land surface. Through continuous eddy covariance (EC) measurements at seven grassland sites in Northern China, this study examined the seasonal and interannual variations of gross primary production (GPP), evapotranspiration (ET) and WUE across four typical grassland ecosystems along a water availability gradient. The highest WUE occurred at the alpine meadow ecosystem with 1.45 g C kg^?1 H₂O, followed by the temperate meadow steppe and the typical steppe. The desert steppe had the lowest WUE with 0.53 g C kg^?1 H₂O. In addition, the remotely-derived WUE estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Breathing Earth System Simulator (BESS) GPP and ET products, were used to characterize the variability in tower-based WUE over these grassland ecosystems. Generally, WUE_BESS had more consistent seasonal trajectories with WUE_EC at most grassland sites compared to the variability of WUE_MOD. The highest square of Pearson correlation coefficient (R²) values of WUE_BESS were achieved in the alpine meadow sites (approximately 0.83), as well as the lowest root mean square error (RMSE), which ranged from 0.21 to 0.37 g C kg^?1 H₂O. However, the performances of both WUE_BESS and WUE_MOD lacked skills at the desert steppe sites which had low vegetation productivity. These remotely-derived WUE products, particularly the WUE_MOD, tended to overestimate the annual mean WUE_EC across these grassland types, with exception of the alpine meadow sites, where exhibited good performance. The underlying reasons for the biases of the MODIS- and BESS-based products in capturing the seasonal dynamics of grassland WUE were also examined. In general, GPP_MOD performed better than GPP_BESS over an 8-day period, whereas ET_BESS had a higher accuracy compared to ET_MOD across the different grassland ecosystems. Our analyses may be useful for improving the remote sensing-based GPP and ET products to accurately monitor the ecosystem WUE patterns of grasslands over large areas.     

基于HJ-1CCD影像的呼伦贝尔草原区MODIS/FPAR产品验证与分析

植物吸收性光合有效辐射分量(FPAR)是描述植被结构以及与之相关的物质与能量交换过程的基本生理变量。选取内蒙古呼伦贝尔谢尔塔拉镇针茅和羊草草甸草原为研究对象,利用2013年5次地面实测实验,通过HJ-I CCD高分辨率卫星影像建立统计模型,从而实现对该研究区MODIS/FPAR产品的验证与分析。1km HJ/FPAR"真值"与MODIS/FPAR产品值的变化趋势基本一致,并且二者具有较好的一致性,R2达到了0.6762。MODIS/FPAR产品能够很好地反映呼伦贝尔草甸草原在整个生长季的长势及物候变化,这是因为研究区样地尺度上HJ/FPAR和MODIS/FPAR产品值不但变化趋势相一致,而且相关系数R2高达0.9148。无论在同尺度(1km)还是整个研究区尺度,MODIS/FPAR均有一定的高估现象。研究结果对了解和进一步使用该地区的MODIS/FPAR产品具有重要的指导意义。     

Temporal and spatial variations of grassland desertification monitoring in Tibet of China

Tibet, the largest region of the Qinghai–Tibet Plateau, is undergoing extensive grassland deterioration and desertification due to both human and natural factors. Alpine meadow and grassland restoration is difficult after degradation; consequently, the desertification of the Tibetan grassland has attracted substantial social attention. This article considered Amdo, Baingoin, Coqên, and Zhongba counties in Tibet as the study areas, employed remote-sensing data, and developed Tibetan grassland desertification classification indices based on field surveys. Moreover, this study used spectral mixture analysis (SMA) methods to interpret remote-sensing image data from the study areas during three periods (1990, 2000, and 2009) and considered the bare sand (gravel) area proportion as the main basis for the evaluation of grassland desertification. The results of this study demonstrate that the slightly, moderately, and severely desertified grasslands of the monitoring zone covered a total area of 114,113.16 km² in 1990, accounting for 82.12% of the study area. The area exhibited no change in 2000 and decreased by 4472.31 km² in 2009. The severely desertified grassland area declined from 1990 to 2009. The degree of grassland desertification in these four Tibetan counties diminished from 1990 to 2009, and the grassland desertification area exhibited a gradual reduction during the same period. Regarding other soil coverage types, the ice and snow area markedly changed and declined to approximately one-third of its original extent during these 20 years, and most of the ice and snow area was converted to bare land and various types of desertified grassland.     

Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data

The eddy covariance technique provides measurements of net ecosystem exchange (NEE) of CO₂ between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number of CO₂ eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO₂ flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai-Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai-Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales.     

赣南客家民居探议

本文就赣南客家民居的类型作了详细的概述,同时针对赣南围屋的特点作了分析,并与闽、粤一带的围屋做了比较,从中可以了解赣南客家民居所反映出赣南客家文化风情、风韵和风采。